1. Field of the Invention
The present invention relates generally to systems and methods for call handling, and more particularly for extracting demographic information.
2. Discussion of Background Art
Automated call handling systems, such as Interactive Voice Response (IVR) systems, using Automatic Speech Recognition (ASR) and Text-to-speech (TTS) software are increasingly important tools for providing information and services to contacts in a more cost efficient manner. IVR systems are typically hosted by a server that includes an array of Digital Signal Processors (DSPs) and enable contacts to interact with corporate databases and services over a telephone using a combination of voice utterances and telephone button presses. IVR systems are particularly cost effective when a large number of contacts require data or services that are very similar in nature, such as banking account checking, ticket reservations, etc., and thus can be handled in an automated manner often providing a substantial cost savings due to a need for fewer human operators.
Knowledge of a contact's demographic characteristics within a call center however would be very valuable. Such demographic information enables IVR systems to make smarter decisions when providing information to contacts. For instance, advertisements are preferably targeted to a demographically well-defined group of people (e.g. young adults, woman under 50, or retired people). However, directly prompting contacts for such information is typically not desirable and so currently advertisements are not very demographically specialized. A contact's demographic information is also useful for tailoring the UVR system's responses to the contact's characteristics, such as avoiding fancy prompts with a tense contact or selecting the contact's gender as the synthetic voice generated by the IVR system. Similarly, the vocabulary and jargon used by the UVR system could also be adapted to the contact, and stressed callers (i.e. “contacts”) could be considered when selecting an operator to handle the contact's call.
Accurately identifying a contact's demographic characteristic, however, is actually a very difficult problem. Many current systems for demographic classification use acoustic classifiers. Acoustic classifiers extract voice features from a contact's speech signal in an attempt to distinguish one or more of a contact's demographic characteristics, such as gender, age, accent, emotional state, etc. However, acoustic classifiers often have such a high error rate that many IVR systems will not deploy them. For instance, a company that repeatedly presents a demographically incorrect type of information to a contact, such as playing male-targeted ads for females, will reflect poorly on a contact's perception of that company.
In response to the concerns discussed above, what is needed is a system and method for extracting demographic information that overcomes the problems of the prior art.